Software (e.g., Microsoft's MapPoint or Rand McNally's MapControl or MapEngine) for routing vehicles, men, and/or equipment (hereafter “resources”) to different sites where they are needed (hereafter “tasks”) over determinate time periods has generally focused on simple route optimization techniques rather than providing a global solution to the allocation problem. Such route optimization systems require that a set of geographic points be fed to the optimizer, with the first and last points being predetermined. With a minimum set of four points, such route optimizers have the opportunity to process all possible route permutations to determine which permutation provides the shortest route. The determination of the distal route points, and the assignment of the intermediate tasks to a determinate resource, must be handled (usually manually) prior to feeding these inputs to the route optimizer.
Factors associated with the determination of which tasks are to be assigned to which resource include, but are not limited to, the following: the urgency or priority of the task, the preferred time band in which the task must be assigned, the complexity of the task being matched with the complexity rating of the resource (e.g., a mechanic trained to handle a particularly difficult task), any preloaded distal points (a preference that a task be the first on the stack, known colloquially as a “first call” parameter), the availability of the resource, the available time spans throughout the day during which the resource is available, the length of time accorded to the task, and the routing length. While traditionally handled manually, there is a need for methods to automate the process by which tasks are assigned to properly qualified and allocated resources. The implementation of such an method improves the overall enterprise efficiency over that of simple route optimization techniques, such that the vehicles travel shorter distances aggregated over the course of time, resulting in (1) savings in wear and tear on vehicles, (2) savings on gasoline, and (3) the possibility for increasing available time for additional tasks to be allocated to the more-efficiently scheduled resource. The net improvement in overall enterprise productivity thereby introduced is of considerable value over a broad range of application spaces across many different industries